Methods and apparatus for generating signatures

ABSTRACT

Signaturing methods and apparatus as described. An example method includes applying a first function to a portion of digital data to produce a first windowed block, applying a second function different from the first function to the same portion of the digital data to produce a second windowed block, determining a first characteristic of a band of frequencies in the first windowed block, determining a second characteristic of the band of frequencies in the second windowed block, comparing the first characteristic to the second characteristic, and assigning a signature bit representative of the portion of the digital data based on the comparison of the first characteristic and the second characteristic.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent arises from a continuation of U.S. patent application Ser.No. 12/266,380, filed Nov. 6, 2008, (now U.S. Pat. No. 8,600,531) andclaims the benefit of U.S. Provisional Patent Application 61/033,992,filed Mar. 5, 2008. U.S. Pat. No. 8,600,531 and U.S. Provisional PatentApplication 61/033,992 are hereby incorporated by reference in theirentireties.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to media monitoring, multimediacontent search and retrieval and, more particularly, to methods andapparatus for generating signatures for use in identifying mediainformation.

BACKGROUND

Identifying media information and, more specifically, audio signals(e.g., information in audio streams) using signature matching techniquesis well established. Signatures are also equivalently known, andfrequently referred to, as fingerprints. Signature matching techniquesare often used in television and radio audience metering applicationsand are implemented using several methods for generating and matchingsignatures. For example, in television audience metering applications,signatures are generated at monitoring sites (e.g., monitoredhouseholds) and reference sites. Monitoring sites typically includelocations such as, for example, households where the media consumptionof audience members is monitored. For example, at a monitoring site,monitored signatures may be generated based on audio streams associatedwith a selected channel, radio station, etc. The monitored signaturesmay then be sent to a central data collection facility for analysis. Ata reference site, signatures, typically referred to as referencesignatures, are generated based on known programs that are providedwithin a broadcast region. The reference signatures may be stored at thereference site and/or a central data collection facility and comparedwith monitored signatures generated at monitoring sites. A monitoredsignature may be found to match with a reference signature and the knownprogram corresponding to the matching reference signature may beidentified as the program that was presented at the monitoring site.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B illustrate example audio stream identification systemsfor generating signatures and identifying audio streams.

FIG. 2 is a flow diagram illustrating an example signature generationprocess.

FIG. 3 is a time-domain representation of an example monitored audiostream.

FIG. 4 is a plot of an example of a portion of the monitored audiostream (i.e., an audio block) that is a sinusoid.

FIG. 5 is a plot of an example window that may be applied to the audioblock of FIG. 4.

FIG. 6 is a plot of a windowed audio block resulting from an applicationof the window of FIG. 5 to the audio block of FIG. 4.

FIG. 7 is a plot of a second example window that may be applied to theaudio block of FIG. 4.

FIG. 8 is a plot of a windowed audio block resulting from an applicationof the window of FIG. 7 to the audio block of FIG. 4.

FIG. 9 is a plot of the window of FIG. 5 showing the correspondingfrequency response of the window.

FIG. 10 is a plot of the window of FIG. 7 showing the correspondingfrequency response of the window.

FIG. 11A is a plot of a second alternate example window.

FIG. 11B is a plot of a corresponding frequency response of the windowof FIG. 11A.

FIG. 12A is a plot of a third alternate example window.

FIG. 12B is a plot of a corresponding frequency response of the windowof FIG. 12A.

FIG. 13 is a flow diagram of an example signature matching process.

FIG. 14 is a diagram showing how signatures may be compared inaccordance with the flow diagram of FIG. 13.

FIG. 15 is a block diagram of an example signature generation system forgenerating signatures based on audio streams or audio blocks.

FIG. 16 is a block diagram of an example signature comparison system forcomparing signatures.

FIG. 17 is a block diagram of an example processor system that may beused to implement the methods and apparatus described herein.

DETAILED DESCRIPTION

Although the following discloses example systems implemented using,among other components, software executed on hardware, it should benoted that such systems are merely illustrative and should not beconsidered as limiting. For example, it is contemplated that any or allof these hardware and software components could be embodied exclusivelyin hardware, exclusively in software, or in any combination of hardwareand software. Accordingly, while the following describes examplesystems, persons of ordinary skill in the art will readily appreciatethat the examples provided are not the only way to implement suchsystems.

The methods and apparatus described herein generally relate togenerating digital signatures that may be used to identify mediainformation. A digital signature, or digital fingerprint, is a signaldescriptor that accurately characterizes signals for the purpose ofmatching, indexing, or database search and retrieval. In particular, thedisclosed methods and apparatus are described with respect to generatingdigital audio signatures based on audio streams or audio blocks (e.g.,audio information). However, the methods and apparatus described hereinmay also be used to generate digital signatures based on any other typeof signals, time series data, and media information such as, forexample, video information, web pages, still images, computer data, etc.Further, the media information may be associated with broadcastinformation (e.g., television information, radio information, etc.),information reproduced from any storage medium (e.g., compact discs(CD), digital versatile discs (DVD), etc.), or any other informationthat is associated with an audio stream, a video stream, or any othermedia information for which the digital signatures are generated. In oneparticular example, the audio streams are identified based on digitalsignatures including monitored digital signatures generated at amonitoring site (e.g., a monitored household) and reference digitalsignatures generated and/or stored at a reference site and/or a centraldata collection facility.

As described in detail below, the methods and apparatus described hereinidentify media information, including audio streams or any other media,based on digital signatures. The example techniques described hereincompute a signature at a particular time using, for example, a singleaudio block of audio samples, but processes the audio block using two ormore windowing functions to result in two or more windowed audio blocks.Further processing of the windowed audio blocks allows detection of thewindowing effects on the audio spectrum of the audio block. Thesignature values unique or substantially unique to the audio block arederived from the effects of the two or more windowing functions on theaudio block. That is, the example techniques described herein enablecomputation or determination of audio signatures without the use of timedisplaced audio blocks. Of course, the selection of the windowingfunctions may be adjusted, as may be the type of transformations, theirparameters, and/or resolutions used to determine signatures.

As described below in detail, after application of the windowingfunctions to the block of audio samples, frequency components of thewindowed audio blocks are generated by transforming the windowed audioblocks from the time domain to the frequency domain using, for example,a discrete Fourier transformation (DFT) or any other suitable transform(e.g., discrete cosine transform (DCT), modified discrete cosinetransform (MDCT), Haar transform, Walsh transform, etc.), be it based ona Fourier Transform or not. The transform can be used to analyze thefrequency components in the windowed audio blocks and identify thespectral power of each frequency component. The spectral powers may thenbe used to generate digital signatures.

Other techniques may be used after application of the window functionsto the audio blocks. For example, the windowed audio blocks may beprocessed using wavelet transforms that transform audio data from thetime domain to the wavelet domain. In general, wavelet transforms may beused to decompose blocks or frames of data (e.g., time domain audiosamples) into multiple sub-bands, thereby allowing data sets to beanalyzed at various scales and/or resolutions. By separating data intomultiple sub-bands, a wavelet transform may be used to analyze each timeinterval of data at a desired scale or resolution.

Alternatively, rather the applying window functions in the time domainto time domain blocks of audio samples, the windowing could be done inthe frequency domain, wherein a frequency response corresponding to atime domain window may be convolved with the frequency spectrum of anaudio block. If frequency domain processing including a convolution isused, a conversion of the audio block to the frequency domain may becarried out using a Fourier transformation, wherein adjustments are madebetween audio blocks to account for discontinuity. Additionally, if theprocessing and application of the windows are done in the frequencydomain, a time domain window having a frequency characteristic with anumber of non-zero elements (e.g., 3-5 non-zero elements) may beselected.

Monitored signatures may be generated using the above techniques at amonitoring site based on audio streams associated with media information(e.g., a monitored audio stream) that is consumed by an audience or towhich an audience is exposed. For example, a monitored signature may begenerated based on the audio track of a television program or any othermedia presented at a monitoring site. The monitored signature may thenbe communicated to a central data collection facility for comparison toone or more reference signatures.

Reference signatures are generated at a reference site and/or a centraldata collection facility using the above techniques on audio streamsassociated with known media information. The known media information mayinclude media that is broadcast within a region, media that isreproduced within a household, media that is received via the Internet,etc. Each reference signature is stored in a memory with mediaidentification information such as, for example, a song title, a movietitle, etc. When a monitored signature is received at the central datacollection facility, the monitored signature is compared with one ormore reference signatures until a match is found. This match informationmay then be used to identify the media information (e.g., monitoredaudio stream) from which the monitored signature was generated. Forexample, a look-up table or a database may be referenced to retrieve amedia title, a program identity, an episode number, etc. thatcorresponds to the media information from which the monitored signaturewas generated.

In one example, the rates at which monitored signatures and referencesignatures are generated may be different. For example, for processingand other concerns, a monitored signature may be 25% of the data rate ofa reference signature. For example, a 48-bit reference signature may begenerated every 0.032 seconds, which results in a reference data rate of48 bits*31.25/seconds or 187.5 bytes/second. In such an arrangement, a48-bit monitored signature may be generated every 0.128 seconds, whichresults in a monitored data rate of 48 bits*7.8125/seconds or 46.875bytes/second. Of course, in an arrangement in which the data rates ofthe monitored and reference signatures differ, this difference must beaccounted for when comparing monitored signatures with referencesignatures. For example, if the monitoring rate is 25% of the referencerate, each consecutive monitored signature will correspond to everyfourth reference signature.

FIGS. 1A and 1B illustrate example audio stream identification systems100 and 150 for generating digital spectral signatures and identifyingaudio streams. The example audio stream identification systems 100 and150 may be implemented as a television broadcast informationidentification system and a radio broadcast information identificationsystem, respectively. The example audio stream identification system 100includes a monitoring site 102 (e.g., a monitored household), areference site 104, and a central data collection facility 106.

Monitoring television broadcast information involves generatingmonitored signatures at the monitoring site 102 based on the audio dataof television broadcast information and communicating the monitoredsignatures to the central data collection facility 106 via a network108. Reference signatures may be generated at the reference site 104 andmay also be communicated to the central data collection facility 106 viathe network 108. The audio content represented by a monitored signaturethat is generated at the monitoring site 102 may be identified at thecentral data collection facility 106 by comparing the monitoredsignature to one or more reference signatures until a match is found.Alternatively, monitored signatures may be communicated from themonitoring site 102 to the reference site 104 and compared one or morereference signatures at the reference site 104. In another example, thereference signatures may be communicated to the monitoring site 102 andcompared with the monitored signatures at the monitoring site 102.

The monitoring site 102 may be, for example, a household for which themedia consumption of an audience is monitored. In general, themonitoring site 102 may include a plurality of media delivery devices110, a plurality of media presentation devices 112, and a signaturegenerator 114 that is used to generate monitored signatures associatedwith media presented at the monitoring site 102.

The plurality of media delivery devices 110 may include, for example,set top box tuners (e.g., cable tuners, satellite tuners, etc.), PVRdevices, DVD players, CD players, radios, etc. Some or all of the mediadelivery devices 110 such as, for example, set top box tuners may becommunicatively coupled to one or more broadcast information receptiondevices 116, which may include a cable, a satellite dish, an antenna,and/or any other suitable device for receiving broadcast information.The media delivery devices 110 may be configured to reproduce mediainformation (e.g., audio information, video information, web pages,still images, etc.) based on, for example, broadcast information and/orstored information. Broadcast information may be obtained from thebroadcast information reception devices 116 and stored information maybe obtained from any information storage medium (e.g., a DVD, a CD, atape, etc.). The media delivery devices 110 are communicatively coupledto the media presentation devices 112 and configurable to communicatemedia information to the media presentation devices 112 forpresentation. The media presentation devices 112 may include televisionshaving a display device and/or a set of speakers by which audiencemembers consume, for example, broadcast television information, music,movies, etc.

The signature generator 114 may be used to generate monitored digitalsignatures based on audio information, as described in greater detailbelow. In particular, at the monitoring site 102, the signaturegenerator 114 may be configured to generate monitored signatures basedon monitored audio streams that are reproduced by the media deliverydevices 110 and/or presented by the media presentation devices 112. Thesignature generator 114 may be communicatively coupled to the mediadelivery devices 110 and/or the media presentation devices 112 via anaudio monitoring interface 118. In this manner, the signature generator114 may obtain audio streams associated with media information that isreproduced by the media delivery devices 110 and/or presented by themedia presentation devices 112. Additionally or alternatively, thesignature generator 114 may be communicatively coupled to microphones(not shown) that are placed in proximity to the media presentationdevices 112 to detect audio streams. The signature generator 114 mayalso be communicatively coupled to the central data collection facility106 via the network 108.

The network 108 may be used to communicate signatures (e.g., digitalspectral signatures), control information, and/or configurationinformation between the monitoring site 102, the reference site 104, andthe central data collection facility 106. Any wired or wirelesscommunication system such as, for example, a broadband cable network, aDSL network, a cellular telephone network, a satellite network, and/orany other communication network may be used to implement the network108.

As shown in FIG. 1A, the reference site 104 may include a plurality ofbroadcast information tuners 120, a reference signature generator 122, atransmitter 124, a database or memory 126, and broadcast informationreception devices 128. The reference signature generator 122 and thetransmitter 124 may be communicatively coupled to the memory 126 tostore reference signatures therein and/or to retrieve stored referencesignatures therefrom.

The broadcast information tuners 120 may be communicatively coupled tothe broadcast information reception devices 128, which may include acable, an antenna, a satellite dish, and/or any other suitable devicefor receiving broadcast information. Each of the broadcast informationtuners 120 may be configured to tune to a particular broadcast channel.In general, the number of tuners at the reference site 104 is equal tothe number of channels available in a particular broadcast region. Inthis manner, reference signatures may be generated for all of the mediainformation transmitted over all of the channels in a broadcast region.The audio portion of the tuned media information may be communicatedfrom the broadcast information tuners 120 to the reference signaturegenerator 122.

The reference signature generator 122 may be configured to obtain theaudio portion of all of the media information that is available in aparticular broadcast region. The reference signature generator 122 maythen generate a plurality of reference signatures (using, for example,the processing described in greater detail below) based on the audioinformation and store the reference signatures in the memory 126.Although one reference signature generator is shown in FIG. 1, aplurality of reference signature generators may be used in the referencesite 104. For example, each of the plurality of signature generators maybe communicatively coupled to a respective one of the broadcastinformation tuners 120.

The transmitter 124 may be communicatively coupled to the memory 126 andconfigured to retrieve signatures therefrom and communicate thereference signatures to the central data collection facility 106 via thenetwork 108.

The central data collection facility 106 may be configured to comparemonitored signatures received from the monitoring site 102 to referencesignatures received from the reference site 104. In addition, thecentral data collection facility 106 may be configured to identifymonitored audio streams by matching monitored signatures to referencesignatures and using the matching information to retrieve televisionprogram identification information (e.g., program title, broadcast time,broadcast channel, etc.) from a database. The central data collectionfacility 106 includes a receiver 130, a signature analyzer 132, and amemory 134, all of which are communicatively coupled as shown.

The receiver 130 may be configured to receive monitored signatures andreference signatures via the network 108. The receiver 130 iscommunicatively coupled to the memory 134 and configured to store themonitored signatures and the reference signatures therein.

The signature analyzer 132 may be used to compare reference signaturesto monitored signatures. The signature analyzer 132 is communicativelycoupled to the memory 134 and configured to retrieve the monitoredsignatures and the reference signatures from the same. The signatureanalyzer 132 may be configured to retrieve reference signatures andmonitored signatures from the memory 134 and compare the monitoredsignatures to the reference signatures until a match is found. Thememory 134 may be implemented using any machine accessible informationstorage medium such as, for example, one or more hard drives, one ormore optical storage devices, etc.

Although the signature analyzer 132 is located at the central datacollection facility 106 in FIG. 1A, the signature analyzer 132 mayinstead be located at the reference site 104. In such a configuration,the monitored signatures may be communicated from the monitoring site102 to the reference site 104 via the network 108. Alternatively, thememory 134 may be located at the monitoring site 102 and referencesignatures may be added periodically to the memory 134 via the network108 by transmitter 124. Additionally, although the signature analyzer132 is shown as a separate device from the signature generators 114 and122, the signature analyzer 132 may be integral with the referencesignature generator 122 and/or the signature generator 114. Stillfurther, although FIG. 1 depicts a single monitoring site (i.e., themonitoring site 102) and a single reference site (i.e., the referencesite 104), multiple such sites may be coupled via the network 108 to thecentral data collection facility 106.

The audio stream identification system 150 of FIG. 1B may be configuredto monitor and identify audio streams associated with radio broadcastinformation, or any other media. In general, the audio streamidentification system 150 is used to monitor the content that isbroadcast by a plurality of radio stations in a particular broadcastregion. Unlike the audio stream identification system 100 used tomonitor television content consumed by an audience, the audio streamidentification system 150 may be used to monitor music, songs, etc. thatare broadcast within a broadcast region and the number of times thatthey are broadcast. This type of media tracking may be used to determineroyalty payments, proper use of copyrights, etc. associated with eachaudio composition. The audio stream identification system 150 includes amonitoring site 152, a central data collection facility 154, and thenetwork 108.

The monitoring site 152 is configured to receive all radio broadcastinformation that is available in a particular broadcast region andgenerate monitored signatures based on the radio broadcast information.The monitoring site 152 includes the plurality of broadcast informationtuners 120, the transmitter 124, the memory 126, and the broadcastinformation reception devices 128, all of which are described above inconnection with FIG. 1A. In addition, the monitoring site 152 includes asignature generator 156. When used in the audio stream identificationsystem 150, the broadcast information reception devices 128 areconfigured to receive radio broadcast information and the broadcastinformation tuners 120 are configured to tune to the radio broadcaststations. The number of broadcast information tuners 120 at themonitoring site 152 may be equal to the number of radio broadcastingstations in a particular broadcast region.

The signature generator 156 is configured to receive the tuned to audioinformation from each of the broadcast information tuners 120 andgenerate monitored signatures for the same. Although one signaturegenerator is shown (i.e., the signature generator 156), the monitoringsite 152 may include multiple signature generators, each of which may becommunicatively coupled to one of the broadcast information tuners 120.The signature generator 156 may store the monitored signatures in thememory 126. The transmitter 124 may retrieve the monitored signaturesfrom the memory 126 and communicate them to the central data collectionfacility 154 via the network 108.

The central data collection facility 154 is configured to receivemonitored signatures from the monitoring site 152, generate referencesignatures based on reference audio streams, and compare the monitoredsignatures to the reference signatures. The central data collectionfacility 154 includes the receiver 130, the signature analyzer 132, andthe memory 134, all of which are described in greater detail above inconnection with FIG. 1A. In addition, the central data collectionfacility 154 includes a reference signature generator 158.

The reference signature generator 158 is configured to generatereference signatures based on reference audio streams. The referenceaudio streams may be stored on any type of machine accessible mediumsuch as, for example, a CD, a DVD, a digital audio tape (DAT), etc. Ingeneral, artists and/or record producing companies send their audioworks (i.e., music, songs, etc.) to the central data collection facility154 to be added to a reference library. The reference signaturegenerator 158 may read the audio data from the machine accessible mediumand generate a plurality of reference signatures based on each audiowork (e.g., the captured audio 300 of FIG. 3). The reference signaturegenerator 158 may then store the reference signatures in the memory 134for subsequent retrieval by the signature analyzer 132. Identificationinformation (e.g., song title, artist name, track number, etc.)associated with each reference audio stream may be stored in a databaseand may be indexed based on the reference signatures. In this manner,the central data collection facility 154 includes a database ofreference signatures and identification information corresponding to allknown and available song titles.

The receiver 130 is configured to receive monitored signatures from thenetwork 108 and store the monitored signatures in the memory 134. Themonitored signatures and the reference signatures are retrieved from thememory 134 by the signature analyzer 132 for use in identifying themonitored audio streams broadcast within a broadcast region. Thesignature analyzer 132 may identify the monitored audio streams by firstmatching a monitored signature to a reference signature. The matchinformation and/or the matching reference signature are then used toretrieve identification information (e.g., a song title, a song track,an artist, etc.) from a database stored in the memory 134.

Although one monitoring site (e.g., the monitoring site 152) is shown inFIG. 1B, multiple monitoring sites may be communicatively coupled to thenetwork 108 and configured to generate monitored signatures. Inparticular, each monitoring site may be located in a respectivebroadcast region and configured to monitor the content of the broadcaststations within a respective broadcast region.

FIG. 2 is a flow diagram representing an example signature generationprocess 200. As shown in FIG. 2, the signature generation process 200first captures a block of audio that is to be characterized by asignature (block 202). An example time domain plot of audio that may becaptured is shown in FIG. 3 at reference numeral 300. The audio may becaptured from an audio source via, for example, a hardwired connectionto an audio source or via a wireless connection, such as an audiosensor, to an audio source. If the audio source is analog, the capturingincludes sampling the analog audio source using, for example, ananalog-to-digital converter. In one example, the audio source may besampled at a rate of 8 kilohertz (kHz), which is referred to as asampling rate (F_(s)). This means that the analog audio is representedby digital samples thereof that are taken at the rate of eight thousandsamples per second, or every 125 microseconds (us). Each of the audiosamples may be represented by monoaural, 16 bits of resolution.

In one example, an audio block corresponding to 8192 samples is capturedfor processing. At the foregoing sampling rate of 8 kHz, thiscorresponds to 1.024 seconds of audio. However, this is merely oneexample, and the number of samples that are collected may correspond toaudio segments ranging anywhere from approximately 1 second to 2 secondsin duration. Generically, herein the number of captured samples in anaudio block is referred to with the variable N. Thus, in the aboveexample, N=8192 and the time range of audio captured corresponds to t .. . t+N/F_(s). A representation of an audio block is shown in FIG. 4 atreference numeral 402, in which, for example purposes, the audio blockcorresponds to a sinusoid.

After the audio block has been captured (block 202), the process 200applies the first window function, referred to as W₁ (block 204A), tothe audio block to produce a first windowed audio block. Additionally,the process 200 windows the audio block using a second window function,referred to as W₂ (block 204B) to produce a second windowed audio block.For example, the window may be a Gaussian or bell shaped function suchas that shown at reference numeral 502 in FIG. 5, wherein the high andlow ends of W₁ 502 have a zero value and the center of the window 502has a value of one. In one example, the windowing is a sample-wisemultiplication between the values of window function and respectivesamples of the audio block. For example, windowing the audio block 402with the window 502, results in a windowed audio block 602, as shown inFIG. 6, wherein the amplitude of the windowed audio block 602 is zero atthe extremes of the window 502 and is the same amplitude as the audioblock 402 at the center of the windowed audio block 602.

Alternatively, rather the applying window functions in the time domainusing sample-wise multiplication of window functions to the audio block,the windowing could be done in the frequency domain, wherein a frequencyresponse corresponding to a time domain window may be convolved with thefrequency spectrum of an audio block. As noted above, if frequencydomain processing including a convolution is used, a conversion of theaudio block to the frequency domain may be carried out using a Fouriertransformation, wherein adjustments are made between audio blocks toaccount for discontinuity. Additionally, if the processing andapplication of the windows are done in the frequency domain, a timedomain window having a frequency characteristic with a number ofnon-zero elements (e.g., 3-5 non-zero elements) may be selected.

The windows selected for W₁ and W₂ may be complimentary in nature. Forexample, if the window 502 shown in FIG. 5 is selected for W₁, thewindow 702 of FIG. 7 may be selected for W₂. As shown in FIG. 7, thewindow 702 is an inverted version of the window W₁, namelyW₂(k)=1−W₁(k), where k is a sample index in the window domain. Window W₂approaches unity value at the high and low ends of the window 702 andhas a zero value in the center of the window 702. Thus, when the window702 is applied to the audio block 402, a windowed audio block 802, asshown in FIG. 8, results. As shown in FIG. 8, the windowed audio block802 has a zero amplitude in the center thereof, but has an amplitudethat substantially matches the amplitude of the audio block 402 at theextremes of the windowed audio block 802.

As shown in FIGS. 9 and 10, the windows 502 and 702 have respectivefrequency responses, 902 and 1002. Thus, the application of the windows502 and 702 to the audio block (e.g., the audio block 402), affects thespectrum of the audio block. As explained below, it is the differenteffects of different windows on the audio block that are examined todetermine signatures representative of the audio block.

While the windows 502, 702 selected for the description above resemble aHann window and an inverted Hann window, respectively, other windowshapes may be used. For example, as shown in FIGS. 11 and 12, twoasymmetrical windows 1102, 1202 may be selected, wherein a first window1102 occupies an upper half of the windowing space and wherein a secondwindow 1202 occupies a lower half of the windowing space. The frequencyresponses of asymmetrical windows 1102, 1202 are identical as shown inFIGS. 11 and 12 at reference numerals 1104 and 1204, but because thewindows operate on mostly distinct portions of an audio block, theresults of the windowing have different spectral characteristics foraudio signals that are not sinusoidal.

While certain examples of window shapes are described herein, otherwindow shapes may be used. For example, window shapes may be arbitrarilyselected for both the first window and the second window (e.g., W₁ andW₂), wherein the selection is made from a set of window functions. Ofcourse, different windows may be used at different times, provided themonitor and reference sites use the same times. Additionally, more thantwo windows may be used.

Returning to FIG. 2, after the windowing is complete (blocks 204A and204B), the windowed audio blocks are respectively transformed (blocks206A and 206B). In one example, the transformation may be atransformation from the time domain into the frequency domain. Forexample, the N samples of captured audio that have been windowed may beconverted into an audio spectrum that is represented by N/2 complex DFTcoefficients. Alternatively, any suitable transformation, such aswavelet transforms, DCT, MDCT, Haar transforms, Walsh transforms, etc.,may be used.

After the transformations are completed (block 206A and 206B), theprocess 200 characterizes the results of each transform (block 208A and208B). For example, the process may determine the energy in each of K+1different bands of each of the transformation results. That is, theresults of the transformation on the windowed audio block resulting fromthe use of window W₁ (block 206A) may be divided into, for example, 16different bands and the energy in each of the 16 different bands may bedetermined. This may be represented by E_(j)(w1), wherein j ranges from0 to 15, and w1 indicates that the energy is associated with thespectrum resulting from the application of window W₁ to the sampledaudio (i.e., to the audio block). Similarly, the results of thetransformation on the windowed block resulting from the use of window W₂(block 206B) may be divided into, for example, 16 different bands, theenergy of which may be determined and represented as E_(j)(w2), whereinj ranges from 0 to 15, and w2 indicates that the energy is associatedwith the spectrum resulting from the application of window W₂.Alternatively, different spectral characteristics other than energy maybe used to characterize the results. For example, spectral flatness ofenergy distribution may be used.

After each set of transform results has been characterized (blocks 208Aand 208B), the process 210 compares the results of thecharacterizations. For example, the results of the characterizations ofeach band may be subtracted from one another. In one example, anintermediate value may be calculated as d_(j)=E_(j)(w2)−E_(j)(w1),wherein j ranges from 0 to K. Keeping with the specific example above inwhich K =15, an intermediate value d_(j) may be calculated, whereind_(j)=E_(j)(w2)−E_(j)(w1), and j ranges from 0 to 15. Thus, such acomparison results in 16 different intermediate values (e.g., d₀, d₁, d₂. . . d₁₅), wherein each intermediate value is the difference incharacteristics in, for example, similar frequency bands of the spectraresulting from the transformations of the windowed audio blocks.

After the intermediate value has been calculated to represent thecomparison of the characterizations (block 210), the process 200determines signature bits based on the comparisons (block 212). Forexample, a signature bit S_(j) may be assigned a value of 1 if theintermediate value d_(j)>0, and may be assigned a value of 0 otherwise,wherein j ranges from 0 to K. More specifically, as noted in the exampleabove K=15 and, thus, there will be 16 comparisons of intermediatevalues to the value of 0 and, based on those comparisons, a 16 bitsignature will be generated to represent the audio block, which wascaptured at block 202 of FIG. 2. After the signature has been determined(block 212), the process 200 iterates (block 214) and capturesadditional audio (block 202) to develop additional signatures.

While the foregoing describes the selection of a first window (W₁) and asecond window (W₂) and that all signature bits for a block of capturedaudio are determined using the selected windows, other configurationsare possible. For example, some bits of a signature representing theblock of captured audio may be determined using a first pair of windows(e.g., W₁ and W₂), whereas other bits of the signature may be determinedusing a different pair of windows (e.g., W₃ and W₄). Additionally, athird pair of windows (e.g., W₁ and W₃) may be used to determineadditional signature bits. In some cases, a unique pair of windows couldbe selected in a predetermined or arbitrary manner to determine thevalue of each signature bit, so long as those same window pairs wereselected to operate on the same window blocks at the reference site.

The foregoing has described signaturing techniques that may be carriedout to determine signatures representative of a portion of capturedaudio. FIG. 13 shows one example signature matching process 1300 thatmay be carried out to compare reference signatures (i.e., signaturesdetermined at a reference site(s)) to monitored signatures (i.e.,signatures determined at a monitoring site). The ultimate goal ofsignature matching is to find the closest match between a query audiosignature (e.g., monitored audio) and signatures in a database (e.g.,signatures taken based on reference audio). The comparison may becarried out at a reference site, a monitoring site, or any other dataprocessing site having access to the monitored signatures and a databasecontaining reference signatures.

Now turning in detail to the example method of FIG. 13, the exampleprocess 1300 involves obtaining a monitored signature and its associatedtiming (block 1302). As shown in FIG. 14, a signature collection mayinclude a number of monitored signatures, three of which are shown inFIG. 14 at reference numerals 1402, 1404 and 1406. Each of thesignatures is represented by a sigma (σ). Each of the monitoredsignatures 1402, 1404, 1406 may include timing information 1408, 1410,1412, whether that timing information is implicit or explicit.

A query is then made to a database containing reference signatures(block 1304) to identify the signature in the database having theclosest match. In one implementation, the measure of similarity(closeness) between signatures is taken to be a Hamming distance,namely, the number of position at which the values of query andreference bit strings differ. In FIG. 14, a database of signatures andtiming information is shown at reference numeral 1416. Of course, thedatabase 1416 may include any number of different signatures fromdifferent media presentations. An association is then made between theprogram associated with the matching reference signature and the unknownsignature (block 1306).

Optionally, the process 1300 may then establish an offset between themonitored signature and the reference signature (block 1308). The valueof the offset is required in order to make a better, more confident,determination if a block of query signatures 1418 matches well thereference signature. Typically offset values for all signatures in shortquery block are remain almost constant relative to respective referencesignatures due to continuity of monitoring (viewing)

In instances where all of the descriptors of more than one referencesignature are associated with a Hamming distance below the predeterminedHamming distance threshold, more than one monitored signature may needto be matched with respective reference signatures of the possiblematching reference audio streams. It will be relatively unlikely thatall of the monitored signatures generated based on the monitored audiostream will match all of the reference signatures of more than onereference audio stream, and, thus erroneously matching more than onereference audio stream to the monitored audio stream can be prevented.

The example methods, processes, and/or techniques described above may beimplemented by hardware, software, and/or any combination thereof. Morespecifically, the example methods may be executed in hardware defined bythe block diagrams of FIGS. 15 and 16. The example methods, processes,and/or techniques may also be implemented by software executed on aprocessor system such as, for example, the processor system 1610 of FIG.16.

FIG. 15 is a block diagram of an example signature generation system1500 for generating digital spectral signatures. In particular, theexample signature generation system 1500 may be used to generatemonitored signatures and/or reference signatures based on windowing,transforming, characterizing, and comparing, an audio block, asdescribed above. For example, the example signature generation system1500 may be used to implement the signature generators 114 and 122 ofFIG. 1A or the signature generators 156 and 158 of FIG. 1B.Additionally, the example signature generation system 1500 may be usedto implement the example methods of FIG. 2.

As shown in FIG. 15, the example signature generation system 1500includes a sample generator 1502, a timing device 1503, a reference timegenerator 1504, a windower 1506, a transformer 1508, a characteristicdeterminer 1510, a comparator 1512, a signature determiner 1514, storage1516, and a data communication interface 1518, all of which may becommunicatively coupled as shown. The example signature generationsystem 1500 may be configured to obtain an example audio stream, acquirea plurality of audio samples from the example audio stream to form ablock of audio and from that single block of audio, generate a signaturerepresentative thereof.

The sample generator 1502 may be configured to obtain the example audiostream, such as a stream resulting in the captured audio 300 of FIG. 3.The stream 300 may be any analog or digital audio stream. If the exampleaudio stream is an analog audio stream, the sample generator 1502 may beimplemented using an analog-to-digital converter. If the example audiostream is a digital audio stream, the sample generator 1502 may beimplemented using a digital signal processor. Additionally, the samplegenerator 1502 may be configured to acquire and/or extract audio samplesat any desired sampling frequency F_(s). For example, as describedabove, the sample generator may be configured to acquire N samples at 8kHz and may use 16 bits to represent each sample. In such anarrangement, N may be any number of samples such as, for example,N=8192. The sample generator 1502 may also notify the reference timegenerator 1504 when an audio sample acquisition process begins. Thesample generator 1502 communicates samples to the windower 1506.

The timing device 1503 may be configured to generate time data and/ortimestamp information and may be implemented by a clock, a timer, acounter, and/or any other suitable device. The timing device 1503 may becommunicatively coupled to the reference time generator 1504 and may beconfigured to communicate time data and/or timestamps to the referencetime generator 1504. The timing device 1503 may also be communicativelycoupled to the sample generator 1502 and may assert a start signal orinterrupt to instruct the sample generator 1502 to begin collecting oracquiring audio sample data. In one example, the timing device 1503 maybe implemented by a real-time clock having a 24-hour period that trackstime at a resolution of milliseconds. In this case, the timing device1503 may be configured to reset to zero at midnight and track time inmilliseconds with respect to midnight. However, generally timestamps canrepresent complete year, month, day, hour, minute, second information asa number of seconds elapsed from a predetermined moment in the past,such as 00:00 AM, Jan. 1, 2005. A subsecond resolution can be added byderiving from the deterministic aquisition rate of collected audiosignatures

The reference time generator 1504 may initialize a reference time t₀when a notification is received from the sample generator 1502. Thereference time t₀ may be used to indicate the time within an audiostream at which a signature is generated. In particular, the referencetime generator 1504 may be configured to read time data and/or atimestamp value from the timing device 1503 when notified of thebeginning of a sample acquisition process by the sample generator 1502.The reference time generator 1504 may then store the timestamp value asthe reference time t₀.

The windower 1506 applies, for example, two windows to the audio blockoutput from the sample generator 1502. Thus, the results of the windower1506 are two windowed audio blocks. As described above, the windows maybe any sets of windows. However, complimentary windows can be preferredbecause they would easily guarantee that on average the energy bothvalues is the same, that leads to equi-probable bit distribution.

The transformer 1508 may be configured to perform an N point DFT on eachof the windowed audio blocks, wherein N is the number of samplesobtained by the sample generator 1502. For example, if the samplegenerator obtains 8192 samples, the transformer will produce a spectrumfrom the samples wherein the spectrum is represented by 4096complex-valued Fourier coefficients.

The characteristic determiner 1510 may be configured to identify severalfrequency bands (e.g., 16 bands) within the DFT spectrumcharacterization generated by the transformer 1508. The selected bandsmay, but preferably do not, overlap with one another. The bands may beselected according to any technique. Of course, any number of suitablebands may be selected (e.g., 48). The characteristic determiner 1510then determines a characteristic in each of the bands. For example, thecharacteristic determiner 1510 may determine the energy in each band.Thus, the results of the characteristic determiner 1510 are two sets ofcharacteristics for each of, for example, 16 bands. For example, if 16bands are selected, the characteristic determiner 1510 output would be32 energy measures, one for each of the bands in each of the DFTs. Thecharacteristics may be represented by E_(j)(w1) and E_(j)(w2), wherein jranges from 0 to K (e.g., 0 to 15), and w1 and w2 represent window 1 andwindow 2, respectively.

The comparator 1512 compares the characteristics of respective bands todetermine intermediate values. For example, the comparator 1512 maygenerate intermediate values according to d_(j)=E_(j)(w2)−E_(j)(w1),such that energies in respective bands of the DFTs are subtracted fromone another.

The signature determiner 1514 operates on the resulting values from thecomparator 1512 to produce one signature bit for each of theintermediate values. This operation may be very similar or identical tothe process 212 described above in conjunction with FIG. 2. That is, thesignature bit values may be based a comparison of the intermediate valueto zero. The signature bits are output to the storage 1516.

The storage may be any suitable medium for accommodating signaturestorage. For example, the storage 1516 may be a memory such as randomaccess memory (RAM), flash memory, or the like. Additionally oralternatively, the storage 1516 may be a mass memory such as a harddrive, an optical storage medium, a tape drive, or the like.

The storage 1516 is coupled to the data communication interface 1518.For example, if the system 1500 is in a monitoring site (e.g., in aperson's home) the signature information in the storage 1516 may becommunicated to a collection facility, a reference site, or the like,using the data communication interface 1518.

FIG. 16 is a block diagram of an example signature comparison system1600 for comparing digital spectral signatures. In particular, theexample signature comparison system 1600 may be used to comparemonitored signatures with reference signatures. For example, the examplesignature comparison system 1600 may be used to implement the signatureanalyzer 132 of FIG. 1A to compare monitored signatures with referencesignatures. Additionally, the example signature comparison system 1600may be used to implement the example process of FIG. 13.

The example signature comparison system 1600 includes a monitoredsignature receiver 1602, a reference signature receiver 1604, acomparator 1606, a Hamming distance filter 1608, a media identifier1610, and a media identification look-up table interface 1612, all ofwhich may be communicatively coupled as shown.

The monitored signature receiver 1602 may be configured to obtainmonitored signatures via the network 108 (FIG. 1) and communicate themonitored signatures to the comparator 1606. The reference signaturereceiver 1604 may be configured to obtain reference signatures from thememory 134 (FIGS. 1A and 1B) and communicate the reference signatures tothe comparator 1606.

The comparator 1606 and the Hamming distance filter 1608 may beconfigured to compare reference signatures to monitored signatures usingHamming distances. In particular, the comparator 1606 may be configuredto compare descriptors of monitored signatures with descriptors from aplurality of reference signatures and to generate Hamming distancevalues for each comparison. The Hamming distance filter 1608 may thenobtain the Hamming distance values from the comparator 1606 and filterout non-matching reference signatures based on the Hamming distancevalues.

After a matching reference signature is found, the media identifier 1610may obtain the matching reference signature and in cooperation with themedia identification look-up table interface 1612 may identify the mediainformation associated with an unidentified audio stream (e.g., theexample monitored audio stream 300 of FIG. 3). For example, the mediaidentification look-up table interface 1612 may be communicativelycoupled to a media identification look-up table or a database that isused to cross-reference media identification information (e.g., movietitle, show title, song title, artist name, episode number, etc.) basedon reference signatures. In this manner, the media identifier 1610 mayretrieve media identification information from the media identificationdatabase based on the matching reference signatures.

FIG. 17 is a block diagram of an example processor system 1710 that maybe used to implement the apparatus and methods described herein. Asshown in FIG. 17, the processor system 1710 includes a processor 1712that is coupled to an interconnection bus or network 1714. The processor1712 includes a register set or register space 1716, which is depictedin FIG. 17 as being entirely on-chip, but which could alternatively belocated entirely or partially off-chip and directly coupled to theprocessor 1712 via dedicated electrical connections and/or via theinterconnection network or bus 1714. The processor 1712 may be anysuitable processor, processing unit or microprocessor. Although notshown in FIG. 17, the system 1710 may be a multi-processor system and,thus, may include one or more additional processors that are identicalor similar to the processor 1712 and that are communicatively coupled tothe interconnection bus or network 1714.

The processor 1712 of FIG. 17 is coupled to a chipset 1718, whichincludes a memory controller 1720 and an input/output (I/O) controller1722. As is well known, a chipset typically provides I/O and memorymanagement functions as well as a plurality of general purpose and/orspecial purpose registers, timers, etc. that are accessible or used byone or more processors coupled to the chipset. The memory controller1720 performs functions that enable the processor 1712 (or processors ifthere are multiple processors) to access a system memory 1724 and a massstorage memory 1725.

The system memory 1724 may include any desired type of volatile and/ornon-volatile memory such as, for example, static random access memory(SRAM), dynamic random access memory (DRAM), flash memory, read-onlymemory (ROM), etc. The mass storage memory 1725 may include any desiredtype of mass storage device including hard disk drives, optical drives,tape storage devices, etc.

The I/O controller 1722 performs functions that enable the processor1712 to communicate with peripheral input/output (I/O) devices 1726 and1728 via an I/O bus 1730. The I/O devices 1726 and 1728 may be anydesired type of I/O device such as, for example, a keyboard, a videodisplay or monitor, a mouse, etc. While the memory controller 1720 andthe I/O controller 1722 are depicted in FIG. 17 as separate functionalblocks within the chipset 1718, the functions performed by these blocksmay be integrated within a single semiconductor circuit or may beimplemented using two or more separate integrated circuits.

The methods described herein may be implemented using instructionsstored on a computer readable medium that are executed by the processor1712. The computer readable medium may include any desired combinationof solid state, magnetic and/or optical media implemented using anydesired combination of mass storage devices (e.g., disk drive),removable storage devices (e.g., floppy disks, memory cards or sticks,etc.) and/or integrated memory devices (e.g., random access memory,flash memory, etc.).

Although certain methods, apparatus, and articles of manufacture havebeen described herein, the scope of coverage of this patent is notlimited thereto.

What is claimed is:
 1. A method, comprising: applying a first functionto a portion of digital data to produce a first windowed block; applyinga second function different from the first function to the same portionof the digital data to produce a second windowed block; determining afirst characteristic of a band of frequencies in the first windowedblock; determining a second characteristic of the band of frequencies inthe second windowed block; comparing the first characteristic to thesecond characteristic; and assigning a signature bit representative ofthe portion of the digital data based on the comparison of the firstcharacteristic and the second characteristic.
 2. A method as defined inclaim 1, wherein the first and second functions comprise complimentarywindow functions.
 3. A method as defined in claim 1, wherein the firstwindow function and the second window function are selected from a setof window functions.
 4. A method as defined in claim 1, wherein thedigital data includes at least one of time series data, videoinformation, a web page, a still image, or computer data.
 5. A method asdefined in claim 1, wherein the first and second characteristicscomprise spectral flatness of the first and second windowed blocks. 6.An apparatus to generate a signature representing digital data, theapparatus comprising: a windower to apply a first window function to aportion of digital data to produce a first windowed block and to apply asecond window function to the portion of the digital data to produce asecond windowed block; a characteristic determiner to determine a firstcharacteristic of a band of frequencies in the first windowed block andto determine a second characteristic of the band of frequencies in thesecond windowed block; a comparator to compare the first characteristicto the second characteristic; and a signature determiner to assign asignature bit representative of the portion of the digital data based onthe comparison of the first characteristic and the secondcharacteristic.
 7. An apparatus as defined in claim 6, wherein the firstand second functions comprise complimentary window functions.
 8. Anapparatus as defined in claim 6, wherein the first window function andthe second window function are selected from a set of window functions.9. An apparatus as defined in claim 6, wherein the digital data includesat least one of time series data, video information, a web page, a stillimage, or computer data.
 10. An apparatus as defined in claim 6, whereinthe first and second characteristics comprise spectral flatness of thefirst and second windowed blocks.
 11. A computer readable storage mediumcomprising computer readable instructions which, when executed, cause aprocessor to at least: apply a first function to a portion of digitaldata to produce a first windowed block; apply a second functiondifferent from the first function to the same portion of the digitaldata to produce a second windowed block; determine a firstcharacteristic of a band of frequencies in the first windowed block;determine a second characteristic of the band of frequencies in thesecond windowed block; compare the first characteristic to the secondcharacteristic; and assign a signature bit representative of the portionof the digital data based on the comparison of the first characteristicand the second characteristic.
 12. A storage medium as defined in claim11, wherein the first and second functions comprise complimentary windowfunctions.
 13. A storage medium as defined in claim 11, wherein thefirst window function and the second window function are selected from aset of window functions.
 14. A storage medium as defined in claim 11,wherein the digital data includes at least one of time series data,video information, a web page, a still image, or computer data.
 15. Astorage medium as defined in claim 11, wherein the first and secondcharacteristics comprise spectral flatness of the first and secondwindowed blocks.